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CUDA implementation of fractal image compression by Al Sideiri A., Alzeidi N., Al Hammoshi M., Chauhan M.S., AlFarsi G.

Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…Specifically, it can go beyond the regular generic description of a plant, integrating the organ-specific features together with the generic features to explicitly force the designed network to focus on the organ regions during species classification. …”
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Automated classification radiograph of Periodontal bone loss using deep learning by Al Husaini, Mohammed Abdulla Salim, Habaebi, Mohamed Hadi, Yadav, Seema

“…The training process was conducted using MATLAB on a Dell computer equipped with a GeForce RTX 4060 GPU. Image data augmentation was applied to increase dataset diversity. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Camera geometry determination based on circular's shape for peg-in-hole task by Farah Adiba, Azman

“…In conclusion, a total of 7 analysis consist of image pre-processing, image segmentation, object classification, comparison between CHT and MCHT, illumination measurement, distance calculation and yaw angle analysis were experimentally tested including the comparison with the existing method. …”
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Vision-based autonomous robot body alignment for copper wire spool pick up by Daud, Mohd Razali, Shalfarina, Shahriman, Mohd Faudzi, Ahmad Afif, Sulaiman, Mohd Herwan, Irawan, Addie, Musa, Zulkifli

“…In conclusion, a total of 7 analysis consist of image preprocessing, image segmentation, object classification, comparison between CHT and MCHT, illumination measurement, distance calculation and yaw angle analysis were experimentally tested including the comparison with the existing method. …”
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Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad by Mohammad, Norhasmira

“…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". The methodology is comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental radiographs, segmentation, and classification of mandibular premolars according to Demirjian's staging system using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. …”
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Short term load forecasting using a hybrid neural network by Yap K.S., Abidin I.Z., Lim C.P., Shah M.S.

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